Model fit

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Assumption checks

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Indices of model fit

Metric	Value
AIC	10668.92
AICc	10669.06
BIC	10778.65
R2 (cond.)	0.19
R2 (marg.)	0.18
ICC	0.01
RMSE	0.74
Sigma	0.74

For interpretation of performance metrics, please refer to this documentation.

Parameter estimates

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# Fixed Effects
Parameter	Coefficient	SE	95% CI	t(4680)	p
(Intercept)	1.36	0.09	(1.17, 1.54)	14.47	< .001
desigualdad apod	0.03	0.01	(5.67e-03, 0.05)	2.49	0.013
esfuerzo esc	0.01	0.02	(-0.02, 0.05)	0.72	0.470
inteligencia esc	0.03	0.01	(1.58e-04, 0.05)	1.97	0.049
esfuerzo soc	0.08	0.02	(0.04, 0.12)	4.27	< .001
merito soc	0.11	0.02	(0.08, 0.15)	6.07	< .001
inteligencia soc	0.26	0.02	(0.23, 0.30)	14.49	< .001
educacion rec [Educación secundaria]	0.07	0.04	(-0.02, 0.15)	1.56	0.119
educacion rec [Educación técnica]	0.05	0.05	(-0.05, 0.14)	1.01	0.313
educacion rec [Universidad o postgrado]	0.12	0.05	(0.02, 0.21)	2.30	0.021
educacion rec [Ns/Nr]	0.09	0.04	(1.98e-03, 0.17)	2.01	0.045
cod depe2 [Part. subvencionado]	2.53e-03	0.03	(-0.06, 0.06)	0.08	0.936
cod depe2 [Part. privado]	0.01	0.06	(-0.10, 0.13)	0.22	0.826
cod grupo rec [Medio]	0.04	0.04	(-0.03, 0.11)	1.02	0.306
cod grupo rec [Alto]	0.16	0.04	(0.08, 0.24)	4.04	< .001

# Random Effects
Parameter	Coefficient
SD (Intercept: mrbd)	0.08
SD (Residual)	0.74

To find out more about table summary options, please refer to this documentation.

Predicted Values

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Model-based Expectation
desigualdad_apod	mrbd	Predicted	SE	95% CI
-1.03	0.00	2.69
0.02	0.00	2.71
1.06	0.00	2.74
2.10	0.00	2.77
3.14	0.00	2.80
4.18	0.00	2.82
5.22	0.00	2.85
6.26	0.00	2.88
7.30	0.00	2.91
8.34	0.00	2.94

Variable predicted: desigualdad

Predictors modulated: desigualdad_apod

Predictors controlled: esfuerzo_esc (3.7), inteligencia_esc (3), esfuerzo_soc (2.7), merito_soc (2.6), inteligencia_soc (2.7), educacion_rec (1), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
esfuerzo_esc	mrbd	Predicted	SE	95% CI
1.28	0.00	2.76
1.88	0.00	2.77
2.48	0.00	2.78
3.08	0.00	2.79
3.68	0.00	2.80
4.28	0.00	2.81
4.88	0.00	2.81
5.48	0.00	2.82
6.08	0.00	2.83
6.68	0.00	2.84

Variable predicted: desigualdad

Predictors modulated: esfuerzo_esc

Predictors controlled: desigualdad_apod (3.1), inteligencia_esc (3), esfuerzo_soc (2.7), merito_soc (2.6), inteligencia_soc (2.7), educacion_rec (1), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
inteligencia_esc	mrbd	Predicted	SE	95% CI
-0.32	0.00	2.71
0.51	0.00	2.73
1.34	0.00	2.75
2.17	0.00	2.77
3.01	0.00	2.80
3.84	0.00	2.82
4.67	0.00	2.84
5.50	0.00	2.86
6.33	0.00	2.89
7.16	0.00	2.91

Variable predicted: desigualdad

Predictors modulated: inteligencia_esc

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), esfuerzo_soc (2.7), merito_soc (2.6), inteligencia_soc (2.7), educacion_rec (1), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
esfuerzo_soc	mrbd	Predicted	SE	95% CI
-0.69	0.00	2.52
0.16	0.00	2.59
1.00	0.00	2.66
1.85	0.00	2.73
2.69	0.00	2.80
3.54	0.00	2.87
4.39	0.00	2.94
5.23	0.00	3.01
6.08	0.00	3.08
6.92	0.00	3.15

Variable predicted: desigualdad

Predictors modulated: esfuerzo_soc

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), inteligencia_esc (3), merito_soc (2.6), inteligencia_soc (2.7), educacion_rec (1), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
merito_soc	mrbd	Predicted	SE	95% CI
-0.81	0.00	2.41
0.04	0.00	2.51
0.89	0.00	2.60
1.75	0.00	2.70
2.60	0.00	2.80
3.45	0.00	2.89
4.30	0.00	2.99
5.16	0.00	3.09
6.01	0.00	3.18
6.86	0.00	3.28

Variable predicted: desigualdad

Predictors modulated: merito_soc

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), inteligencia_esc (3), esfuerzo_soc (2.7), inteligencia_soc (2.7), educacion_rec (1), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
inteligencia_soc	mrbd	Predicted	SE	95% CI
-0.67	0.00	1.91
0.17	0.00	2.13
1.02	0.00	2.35
1.86	0.00	2.58
2.70	0.00	2.80
3.55	0.00	3.02
4.39	0.00	3.24
5.24	0.00	3.46
6.08	0.00	3.68
6.93	0.00	3.91

Variable predicted: desigualdad

Predictors modulated: inteligencia_soc

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), inteligencia_esc (3), esfuerzo_soc (2.7), merito_soc (2.6), educacion_rec (1), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
educacion_rec	mrbd	Predicted	SE	95% CI
8vo grado o menos	0.00	2.80
Educación secundaria	0.00	2.87
Educación técnica	0.00	2.85
Universidad o postgrado	0.00	2.91
Ns/Nr	0.00	2.89

Variable predicted: desigualdad

Predictors modulated: educacion_rec

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), inteligencia_esc (3), esfuerzo_soc (2.7), merito_soc (2.6), inteligencia_soc (2.7), cod_depe2 (1), cod_grupo_rec (1)

Model-based Expectation
cod_depe2	mrbd	Predicted	SE	95% CI
Municipal	0.00	2.80
Part. subvencionado	0.00	2.80
Part. privado	0.00	2.81

Variable predicted: desigualdad

Predictors modulated: cod_depe2

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), inteligencia_esc (3), esfuerzo_soc (2.7), merito_soc (2.6), inteligencia_soc (2.7), educacion_rec (1), cod_grupo_rec (1)

Model-based Expectation
cod_grupo_rec	mrbd	Predicted	SE	95% CI
Bajo	0.00	2.80
Medio	0.00	2.84
Alto	0.00	2.96

Variable predicted: desigualdad

Predictors modulated: cod_grupo_rec

Predictors controlled: desigualdad_apod (3.1), esfuerzo_esc (3.7), inteligencia_esc (3), esfuerzo_soc (2.7), merito_soc (2.6), inteligencia_soc (2.7), educacion_rec (1), cod_depe2 (1)

Text reports

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Textual summary

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with desigualdad_apod (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to desigualdad_apod = 0, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with esfuerzo_esc (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to esfuerzo_esc = 0, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with inteligencia_esc (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to inteligencia_esc = 0, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with esfuerzo_soc (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to esfuerzo_soc = 0, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with merito_soc (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to merito_soc = 0, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with inteligencia_soc (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to inteligencia_soc = 0, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with educacion_rec (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to educacion_rec = 8vo grado o menos, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation., We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with cod_depe2 (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to cod_depe2 = Municipal, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation. and We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict desigualdad with cod_grupo_rec (formula: desigualdad ~ 1 + desigualdad_apod + esfuerzo_esc + inteligencia_esc + esfuerzo_soc + merito_soc + inteligencia_soc + educacion_rec + cod_depe2 + cod_grupo_rec). The model included mrbd as random effect (formula: ~1 | mrbd). The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to cod_grupo_rec = Bajo, is at 1.36 (95% CI (1.17, 1.54), t(4680) = 14.47, p < .001). Within this model:

The effect of desigualdad apod is statistically significant and positive (beta = 0.03, 95% CI (5.67e-03, 0.05), t(4680) = 2.49, p = 0.013; Std. beta = 0.03, 95% CI (7.18e-03, 0.06))
The effect of esfuerzo esc is statistically non-significant and positive (beta = 0.01, 95% CI (-0.02, 0.05), t(4680) = 0.72, p = 0.470; Std. beta = 9.78e-03, 95% CI (-0.02, 0.04))
The effect of inteligencia esc is statistically significant and positive (beta = 0.03, 95% CI (1.58e-04, 0.05), t(4680) = 1.97, p = 0.049; Std. beta = 0.03, 95% CI (1.60e-04, 0.05))
The effect of esfuerzo soc is statistically significant and positive (beta = 0.08, 95% CI (0.04, 0.12), t(4680) = 4.27, p < .001; Std. beta = 0.08, 95% CI (0.05, 0.12))
The effect of merito soc is statistically significant and positive (beta = 0.11, 95% CI (0.08, 0.15), t(4680) = 6.07, p < .001; Std. beta = 0.12, 95% CI (0.08, 0.16))
The effect of inteligencia soc is statistically significant and positive (beta = 0.26, 95% CI (0.23, 0.30), t(4680) = 14.49, p < .001; Std. beta = 0.27, 95% CI (0.23, 0.31))
The effect of educacion rec (Educación secundaria) is statistically non-significant and positive (beta = 0.07, 95% CI (-0.02, 0.15), t(4680) = 1.56, p = 0.119; Std. beta = 0.08, 95% CI (-0.02, 0.19))
The effect of educacion rec (Educación técnica) is statistically non-significant and positive (beta = 0.05, 95% CI (-0.05, 0.14), t(4680) = 1.01, p = 0.313; Std. beta = 0.06, 95% CI (-0.06, 0.18))
The effect of educacion rec (Universidad o postgrado) is statistically significant and positive (beta = 0.12, 95% CI (0.02, 0.21), t(4680) = 2.30, p = 0.021; Std. beta = 0.14, 95% CI (0.02, 0.26))
The effect of educacion rec (Ns/Nr) is statistically significant and positive (beta = 0.09, 95% CI (1.98e-03, 0.17), t(4680) = 2.01, p = 0.045; Std. beta = 0.11, 95% CI (2.41e-03, 0.21))
The effect of cod depe2 (Part. subvencionado) is statistically non-significant and positive (beta = 2.53e-03, 95% CI (-0.06, 0.06), t(4680) = 0.08, p = 0.936; Std. beta = 3.08e-03, 95% CI (-0.07, 0.08))
The effect of cod depe2 (Part. privado) is statistically non-significant and positive (beta = 0.01, 95% CI (-0.10, 0.13), t(4680) = 0.22, p = 0.826; Std. beta = 0.02, 95% CI (-0.13, 0.16))
The effect of cod grupo rec (Medio) is statistically non-significant and positive (beta = 0.04, 95% CI (-0.03, 0.11), t(4680) = 1.02, p = 0.306; Std. beta = 0.05, 95% CI (-0.04, 0.13))
The effect of cod grupo rec (Alto) is statistically significant and positive (beta = 0.16, 95% CI (0.08, 0.24), t(4680) = 4.04, p < .001; Std. beta = 0.20, 95% CI (0.10, 0.29))

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald t-distribution approximation.

The model’s total explanatory power is moderate (conditional R2 = 0.19) and the part related to the fixed effects alone (marginal R2) is of 0.18

Column

Model information

---
title: "Regression model summary from `{easystats}`"
output: 
  flexdashboard::flex_dashboard:
    theme:
      version: 4
      # bg: "#101010"
      # fg: "#FDF7F7" 
      primary: "#0054AD"
      base_font:
        google: Prompt
      code_font:
        google: JetBrains Mono
params:
  model: model
  check_model_args: check_model_args
  parameters_args: parameters_args
  performance_args: performance_args
---

```{r setup, include=FALSE}
library(flexdashboard)
library(easystats)

# Since not all regression model are supported across all packages, make the
# dashboard chunks more fault-tolerant. E.g. a model might be supported in
# `{parameters}`, but not in `{report}`.
#
# For this reason, `error = TRUE`
knitr::opts_chunk$set(
  error = TRUE,
  out.width = "100%"
)
```

```{r}
# Get user-specified model data
model <- params$model

# Is it supported by `{easystats}`? Skip evaluation of the following chunks if not.
is_supported <- insight::is_model_supported(model)

if (!is_supported) {
  unsupported_message <- sprintf(
    "Unfortunately, objects of class '%s' are not yet supported in {easystats}.\n
    For a list of supported models, see `insight::supported_models()`.",
    class(model)[1]
  )
}
```


Model fit 
=====================================  

Column {data-width=700}
-----------------------------------------------------------------------

### Assumption checks

```{r check-model, eval=is_supported, fig.height=10, fig.width=10}
check_model_args <- c(list(model), params$check_model_args)
do.call(performance::check_model, check_model_args)
```

```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=300}
-----------------------------------------------------------------------

### Indices of model fit

```{r, eval=is_supported}
# `{performance}`
performance_args <- c(list(model), params$performance_args)
table_performance <- do.call(performance::performance, performance_args)
print_md(table_performance, layout = "vertical", caption = NULL)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

For interpretation of performance metrics, please refer to <a href="https://easystats.github.io/performance/reference/model_performance.html" target="_blank">this documentation</a>.

Parameter estimates
=====================================  

Column {data-width=550}
-----------------------------------------------------------------------

### Plot

```{r dot-whisker, eval=is_supported}
# `{parameters}`
parameters_args <- c(list(model), params$parameters_args)
table_parameters <- do.call(parameters::parameters, parameters_args)

plot(table_parameters)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=450}
-----------------------------------------------------------------------

### Tabular summary

```{r, eval=is_supported}
print_md(table_parameters, caption = NULL)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

To find out more about table summary options, please refer to <a href="https://easystats.github.io/parameters/reference/model_parameters.html" target="_blank">this documentation</a>.


Predicted Values
=====================================  

Column {data-width=600}
-----------------------------------------------------------------------

### Plot

```{r expected-values, eval=is_supported, fig.height=10, fig.width=10}
# `{modelbased}`
int_terms <- find_interactions(model, component = "conditional", flatten = TRUE)
con_terms <- find_variables(model)$conditional

if (is.null(int_terms)) {
  model_terms <- con_terms
} else {
  model_terms <- clean_names(int_terms)
  int_terms <- unique(unlist(strsplit(clean_names(int_terms), ":", fixed = TRUE)))
  model_terms <- c(model_terms, setdiff(con_terms, int_terms))
}

text_modelbased <- lapply(unique(model_terms), function(i) {
  grid <- get_datagrid(model, at = i, range = "grid", preserve_range = FALSE)
  estimate_expectation(model, data = grid)
})

ggplot2::theme_set(theme_modern())
# all_plots <- lapply(text_modelbased, function(i) {
#   out <- do.call(visualisation_recipe, c(list(i), modelbased_args))
#   plot(out) + ggplot2::ggtitle("")
# })
all_plots <- lapply(text_modelbased, function(i) {
  out <- visualisation_recipe(i, show_data = "none")
  plot(out) + ggplot2::ggtitle("")
})

see::plots(all_plots, n_columns = round(sqrt(length(text_modelbased))))
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=400}
-----------------------------------------------------------------------

### Tabular summary

```{r, eval=is_supported, results="asis"}
for (i in text_modelbased) {
  tmp <- print_md(i)
  tmp <- gsub("Variable predicted", "\nVariable predicted", tmp)
  tmp <- gsub("Predictors modulated", "\nPredictors modulated", tmp)
  tmp <- gsub("Predictors controlled", "\nPredictors controlled", tmp)
  print(tmp)
}
```


```{r, eval=!is_supported}
cat(unsupported_message)
```


Text reports
=====================================    

Column {data-width=500}
-----------------------------------------------------------------------

### Textual summary

```{r, eval=is_supported, results='asis', collapse=TRUE}
# `{report}`
text_report <- report(model)
text_report_performance <- report_performance(model)

gsub("]", ")", gsub("[", "(", text_report, fixed = TRUE), fixed = TRUE)
cat("\n")
gsub("]", ")", gsub("[", "(", text_report_performance, fixed = TRUE), fixed = TRUE)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=500}
-----------------------------------------------------------------------

### Model information

```{r, eval=is_supported}
model_info_data <- insight::model_info(model)

model_info_data <- datawizard::data_to_long(as.data.frame(model_info_data))

DT::datatable(model_info_data)
```

```{r, eval=!is_supported}
cat(unsupported_message)
```